Embedding Models
Models that turn text into vectors. Dimensions, context limits and licence terms differ sharply between them, and the choice fixes the quality of every retrieval system built on top.
8 technologies
- OpenAI Text Embedding 3 model Hosted embedding models with configurable output dimensions.
- Cohere Embed model Hosted multilingual embedding model with separate query and document modes.
- BGE model Embedding model family that ranks well on retrieval benchmarks.
- GTE model Embedding model family from Alibaba, trained for retrieval and ranking.
- Jina Embeddings model Embedding models designed around long inputs and multilingual coverage.
- E5 model Text embedding model family trained on weakly supervised pairs.
- Nomic Embed model Open embedding model with an auditable training set and long context.
- Instructor model Embedding model that takes a task instruction alongside the text.